A survey on spatio-temporal framework for kinematic gait analysis in RGB videos

• Published in: Journal of visual communication and image representation 2021-08, Vol.79, p.103218, Article 103218
• Main Authors: Amsaprabhaa, M., Nancy Jane, Y., Khanna Nehemiah, H.
• Format: Article
• Language: English
• Subjects: Gait databases; Gait prediction; Gait recognition representation; Human gait recognition; Kinematic joint points; Spatio-temporal features
• ISSN: 1047-3203; 1095-9076
• DOI: 10.1016/j.jvcir.2021.103218

•This paper presents a comprehensive study on spatiotemporal based-gait analysis.•Describes the outline of historic examination of the gait recognition framework.•Depicts the overview of previous gait databases and gait feature representation.•Evaluating spatio-temporal features to enhance accuracy rate of gait detection.•Comparing the obtained accuracy rate to various databases and classifiers.•Provides a brief explanation of the future perspective of the proposed work. Human gait recognition from videos is one of the promising research topics for analyzing human walking behavior. Spatio-temporal features and kinematics interesting points (three dimensional skeleton points) are the two key metrics in the gait examination. In general, input to gait recognition methods is categorized into 3 groups namely; two dimensional video-based, depth image-based and three dimensional (3D) skeleton-based methods. This work aims to present a survey on spatio-temporal and kinematic gait characteristics based on visual and 3D skeletal traits in RGB videos. A detailed insight on the various benchmarked gait databases, gait recognition representations based on model-based, model-free approaches and classifiers are presented in this review. Also, this paper investigates the performance metrics, application areas and covariate factors that influence the gait recognition process. Finally, the paper outlines the future perspective of gait recognition system based on kinematic joint points.